@article {Yu143081,
author = {Yu, Sung-Huan and Vogel, J{\"o}rg and F{\"o}rstner, Konrad Ulrich},
title = {ANNOgesic: A Pipeline To Translate Bacterial/Archaeal RNA-Seq Data Into High-Resolution Genome Annotations},
year = {2017},
doi = {10.1101/143081},
publisher = {Cold Spring Harbor Laboratory},
abstract = {To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or non-coding RNAs are harder to detect. RNA-Seq has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-Seq data in order to generate high-resolution annotations is challenging, time consuming and requires numerous different steps. We have constructed a powerful and modular pipeline called ANNOgesic that provides the required analyses and simplifies RNA-Seq-based bacterial and archaeal genome annotation. It predicts and annotates numerous features, including small non-coding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pythonhosted.org/ANNOgesic/},
URL = {https://www.biorxiv.org/content/early/2017/05/29/143081},
eprint = {https://www.biorxiv.org/content/early/2017/05/29/143081.full.pdf},
journal = {bioRxiv}
}